Cyclonic low-pressure systems (LPS) produce abundant rainfall in South Asia, where they are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department (IMD) has tracked monsoon depressions for over a century, finding a large decline in their number in recent decades, but their methods have changed over time and do not include monsoon lows. This study presents a fast, objective algorithm for identifying monsoon LPS in high-resolution datasets. Variables and thresholds used in the algorithm are selected to best match a subjectively analyzed LPS dataset while minimizing disagreement between four atmospheric reanalyses in a training period. The streamfunction of the 850 hPa horizontal wind is found to be the best variable for tracking LPS; it is less noisy than vorticity and represents the complete non-divergent wind, even when flow is not geostrophic. Using this algorithm, LPS statistics are computed for five reanalyses, and none show a detectable trend in monsoon depression counts since 1979. Both the Japanese 55-year Reanalysis (JRA-55) and the IMD dataset show a step-like reduction in depression counts when they began using geostationary satellite data, in 1979 and 1982 respectively; the 1958-2018 linear trend in JRA-55, however, is smaller than in the IMD dataset and its error bar includes zero. There are more LPS in seasons with above-average monsoon rainfall and also in La Nin ̵̃a years, but few other large-scale modes of interannual climate variability are found to modulate LPS counts, lifetimes, or track length consistently across all reanalyses.

Advances in the understanding and modelling of surface currents have revealed the importance of mesoscale and submesoscale features. These features should have a large influence on wind waves, and in particular wave heights are expected to be modified by refraction. Still, the quantitative impact of currents on waves is not well known due to the complexity of the random wave fields and currents that are found in the ocean, and the lack of observations of both currents and waves at scales shorter than 150 km. Here we combine novel satellite altimetry data with phase-averaged numerical wave models forced by wind and surface currents fields, taken from the oceanic model CROCO, run at 2.5km resolution. The influence of the spatial resolution of the current field is investigated using smoothed versions of the same current field. We find that a numerical wave model forced with surface currents with resolutions of 30 km or less and a directional resolution of 7.5 degrees or less, can provide accurate representations of the significant wave height gradients found in the Agulhas current. Using smoother current fields, such as derived from satellite measurements of dynamic height, generally underestimates wave height gradients. Hence, satellite altimetry provides high resolution wave height with a gradient magnitude that is a constraint on surface current gradients, at resolutions that may not be resolved by today's combination of mean dynamic topography and altimeter-derived anomalies. Beyond a demonstration for relatively steady currents, this may apply to time-varying currents if enough wave measurements are available.

During 2018-2019, oil was intermittently produced from the Late Jurassic Upper Portland Sandstone in the Weald Basin, southeast England, via the Horse Hill-1 and Brockham-X2Y wells. Concurrently, a sequence of earthquakes of magnitude 3.25 occurred near Newdigate, ~4 km and ~8 km from these wells. The pattern, with earthquakes concentrated during production from this reservoir, suggests a cause-and-effect connection. It is proposed that this seismicity occurred on a patch of fault transecting permeable Dinantian limestone, beneath the Jurassic succession of the Weald Basin, hydraulically connected to the Portland reservoir via this permeable fault and the permeable calcite ‘beef’ fabric within the Portland sandstone; oil production depressurizes this reservoir and draws groundwater from the limestone, compacting it and ‘unclamping’ the fault, reaching the Coulomb failure criterion and causing seismicity. In principle this model is testable, but required data, notably the history of pressure variations in the wells, are not currently in the public domain. The recognition that this instance of seismicity is arguably caused by human activity may well help inform understanding of anthropogenic seismicity in other settings. The initial response, including claims that any connection between this seismicity and oil production was implausible, before any geomechanical analysis was done, was inappropriate.

During tropical cyclones, meteotsunami waves can be triggered by atmospheric disturbances accompanying tropical cyclone rainbands (TCRs). Due to a paucity of high resolution field data along open coasts during these extreme events, relatively little is known about meteotsunami generation by TCRs and the coastal impact of these wave phenomena. Here we link high-resolution field measurements of sea-level and air pressure from Hurricane Harvey (2017) with a numerical model to show that large drops in air pressure accompanying trains of very narrow TCRs can initiate meteotsunami O(40 cm) in height along open coasts distant from the storm center (>200 km). The resonant-amplification and propagation of meteotsunami generated by pressure forcing is highly dependent on oceanographic (storm surge, bathymetry, and coastal morphology) and atmospheric factors (variable TCR forward speed, TCR path of translation). We discover that meteotsunami hazard can extend several days before and after hurricane landfall, and that meteotsunami are more ubiquitous along the open coast than tidal gauge records suggest, likely due to the highly-localized propagation and inherent structure of TCRs. This combined field and numerical study identifies the potential, but sometimes highly localized conditions necessary, for meteotsunami to modify storm processes (e.g., overwash, beach erosion) and serve as a coastal flood hazard during hurricane impact.

Synoptic-scale cyclonic vortices produce abundant rainfall in South Asia, where these low pressure systems (LPS) are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department has tracked monsoon depressions for over a century, finding a large decline in the number of those storms in recent decades; their tracking methods, however, seem to have changed over time and do not include monsoon lows, which can produce intense rainfall despite their weak winds. This study presents a fast and objective tracking algorithm that can identify monsoon LPS in high-resolution datasets with a variety of grid structures. A sensitivity analysis has been performed to select a set of atmospheric variables and their corresponding thresholds for optimal tracking of LPS. Approximately 250 combinations of variables and thresholds are used to identify LPS over roughly a decade (the training period) in each of four atmospheric reanalyses, and these combinations are ranked using a skill score that compares the reanalyses with each other and with a preexisting track dataset that was compiled by subjective identification of LPS. This procedure finds the streamfunction of the 850 hPa horizontal wind to be the best variable for tracking LPS. The streamfunction is smoother than the vorticity field and represents the complete non-divergent component of the wind even when the flow is not geostrophic, unlike the geopotential height or sea level pressure. Using this tracking algorithm, LPS statistics are then computed in five reanalysis products that each span at least 40 years, with a primary goal being to determine whether the large decrease in monsoon depressions seen in the India Meteorological Department track dataset since the 1970s can be found in any reanalysis. This trend assessment is particularly relevant for the ERA5 reanalysis, which extends back to 1950 and which contains explicit climate forcings. In addition to secular trends, this study assesses the decadal variation of LPS, as well as interannual changes in LPS activity that are associated with the El Niño-Southern Oscillation and the Indian Ocean Dipole.

The longitudinal spatial coherence near 1 AU of the magnetic field in sheath regions driven by interplanetary coronal mass ejection (ICME) is studied by investigating ACE and spacecraft measurements of 29 sheaths. During 2000-2002 Wind performed prograde orbits, and the non-radial spacecraft separation varied from 0.001 to 0.012 AU between the studied events. We compare the measurements by computing the Pearson correlation coefficients for the magnetic field magnitude and components, and estimate the magnetic field coherence by evaluating the scale lengths that give the extrapolated distance of zero correlation between the measurements. The correlation is also separately examined for low- and high-pass filtered data. We discover magnetic fields larger scale lengths in ICME sheaths than those reported for the solar wind but, in general, smaller than for the ICME ejecta. Our results imply that magnetic fields in the sheath are more coherently structured and well correlated compared to the solar wind. The largest sheath coherence is reported in the GSE -direction that has the scale length of 0.149 AU while the lengths for Bx, Bz, and |B| vary between 0.024 and 0.035 AU. The same sheath magnitude ordering of scale lengths also apply for the low-pass filtered magnetic field data. We discuss field line draping and the alignment of pre-existing discontinuities by the shock passage giving reasoning for observed results.

Energy exchange at the snow-atmosphere interface in winter is important for the evolution of temperature at the surface and within the snow, preconditioning the snowpack for melt during spring. This study illustrates a set of diagnostic tools that are useful for evaluating the energy exchange at the Earth’s surface in an Earth System Model, from a process-based perspective, using in-situ observations. In particular, a new way to measure model improvement using the response of the surface temperature and other surface energy budget (SEB) terms to radiative forcing is presented. These process-oriented diagnostics also provide a measure of the coupling strength between the incoming radiation and the various terms in the SEB, which can be used to ensure that improvements in predictions of user relevant properties, such as 2m temperature, are happening for the right reasons. Correctly capturing such process relationships is a necessary step towards achieving more skilful weather forecasts and climate projections. These diagnostic techniques are applied to assess the impact of a new multi-layer snow scheme in the European Centre for Medium-Range Weather Forecasts’-Integrated Forecast System at two high-Arctic sites (Summit, Greenland and Sodankylä, Finland). The multi-layer scheme is expected to replace a single layer snow scheme in the operational forecasting system, enhancing the 2m temperature forecast reliability and skill across the northern hemisphere in boreal winter.

Recent developments in space-based surveying methods of Earth’s topography, including the differential synthetic aperture radar interferometry (DInSAR), increased the availability of options for monitoring of land subsidence. However, DInSAR methods require expert knowledge, specialized software, and are time-consuming. Here, we demonstrate that a land subsidence signal in the difference of freely available global digital elevation models (DEMs), e.g., SRTM and TanDEM-X, is identifiable using a simple statistical method. This finding opens up a venue to develop a dedicated computer application to identify land subsidence or uplift of the order > 20 mm yr. Such an application would allow for the monitoring of the impacts of underground mining, earthquakes, landslides, volcanic activities, and similar effects on the Earth’s topography. This software will provide a useful and cost-effective approach to scan the global DEMs for the benefit of many land planning and management agencies around the world.

Coastal areas are highly vulnerable to flooding, due to hydrological extreme events such heavy rainfalls and/or storm surges which are supposed to be increasing in the next future due to the emission in atmosphere of anthropogenic greenhouse gases. In this study, in order to assess the future hydraulic risk in coastal regions, as well as, to identify optimal defense/adaptation policies, a risk analysis model is developed to calculate the present day and future flood risk, accounting for climate change uncertainties and mitigation measures. Such model juxtaposes a number of coupled/nested models as: a) a stacking daily rainfall downscaling model which combines simulations from multiple predictive models, as Random Forest, extreme gradient boosting and Non-homogeneous Hidden Markov Model (NHMM) (Cioffi et al. 2018); b) a Bivariate Point Process model (BPPM) (Zheng et al., 2014) that calculates Joint probability density function between extreme daily rainfall amount and daily extreme storm tide depth; c) a simulation-optimization model - in which multi-objective GA optimization model (Deb et al., 2002) and 2D hydraulic model are combined (Cioffi et al. 2018) - calculates sets of Pareto optimal solutions which are obtained by defining two optimality criteria consisting in: minimizing both the cost of the flood defense infrastructure system and the flooding hydraulic risk. ; d) a mathematical decision model which is aimed to identify the best policies of mitigation of hydraulic risk and the timing, taking into account the uncertainties in hydrological extreme event predictions. The risk analysis model is applied to the study case of Mazzocchio area which is the most depressed area (about 10000 ha) within the Pontinia Plain, a large reclamation region in the south of Lazio (Italy), particularly vulnerable to extreme events - as extreme rainfall amount and sea level rise due to storm surge at the sea outfall of the river- which in the past caused the crisis of hydraulic network system with flooding of large areas and collapse of levees. XXI Century projections of daily rainfall amount and sea level for the RCP 8.5-IPCC scenarios were performed using ensemble of 35 GCM simulations (CESM1 CAM5 BGC 20C + RCP8.5 Large Ensemble) (Kay et al., 2015).

The Quasi-Biennial Oscillation (QBO) dominates the interannual variability in the tropical lower stratosphere and is characterized by the descent of alternating easterly and westerly zonal winds. The QBO impact on tropical clouds and convection has received great attention in recent years due to its implications for weather and climate. In this study, a 15-year record of high vertical resolution observations from CALIPSO are used to document the QBO impact on equatorial (10°S-10°N) clouds. Observations from radio occultations, the CERES instrument, and the ERA5 reanalysis are also used to document the QBO impact on temperature, radiative energy budget, and zonal wind. It is shown that the QBO impact on zonal mean equatorial cloud fraction has a strong seasonality. The strongest cloud fraction response to the QBO occurs in boreal spring and early summer extending down to ~12 km and results in a significant longwave cloud radiative effect anomaly. The seasonality of the cloud fraction changes is synchronized with those of temperature and zonal wind in the tropical upper troposphere.

i) Within the framework of 3D resistive MHD, we simulate the formation of a plasma jet with the morphology, upward velocity and timescale formation similar to those expected for Type II spicules as described in González-Avilés et al. (2018a). ii) In this paper we analyze the transverse displacements and rotational type motion of the jet. iii) We calculate time series of the velocity components in different points near to the jet for various heights and find transverse oscillations in agreement with spicule observations. iv) By analyzing temperature isosurfaces, we find that the line-ofsight (LOS) is approximately perpendicular to the jet axis. v) The jet shows a red-blue shift pattern caused by rotational motion

The aftershock zone of the 1976 7.8 Tangshan earthquake, China, remains seismically active, experiencing moderate events such as the December 5, 2019,4.5 Fengnan event. It is still debated whether aftershock sequences following large earthquakes in low seismicity continental regions can persist for several centuries. To understand the current stage of the Tangshan aftershock sequence, we analyse the sequence record and separate background seismicity from the triggering effect using a finite-source epidemic-type aftershock sequence (FS-ETAS) model. Our results show that the background rate notably decreases after the mainshock. The estimated probability that the most recent 4.5 earthquake (December 5, 2019, Fengnan District, Tangshan) is a background event is 63.8%. This indicates that the contemporary seismicity in the Tangshan aftershock zone can be characterised as a transition from aftershock activity to background seismicity. Although the aftershock sequence is still active in the Tangshan region, it is largely overridden by background seismicity.

The Stratospheric Aerosol and Gas Experiment operating on the International Space Station (SAGE III/ISS) is an occultation instrument that retrieves aerosol extinction and ozone, water vapor, and other trace gas concentrations. Water vapor in the stratosphere plays a significant role in ozone depletion and global temperature regulation making it an important species to monitor. The new SAGE III/ISS instrument provides high quality, vertically resolved profiles of water vapor throughout the stratosphere and upper troposphere. A discussion is presented on the sensitivity of the SAGE III/ISS instrument to water vapor and provide an early evaluation of the retrieved profiles.

Analyses of wildfire-climate relationships over North America were conducted using diverse data including ground-based measurements, satellite retrievals, and re-analyses for the period 1984-2014. Results show the western US (WUS) has experienced the most robust trend in increasing burned area, even though Alaska and central Canada possess comparable or even stronger warming trends compared to WUS. In addition to warming, the WUS has been under the influence of multi-decadal trends in tropospheric relative humidity deficit, reduced cloudiness, increased surface net insolation, enhanced adiabatic warming and drying from increased tropospheric subsidence, as well as drying from enhanced off-shore low-level flow, potentially leading to more abundant dry fuels and raging large wildfires. These trends are likely the manifestation of a regional climate feedback that is enabled by the intensification, and expansion of the North Pacific Subtropical High, associated with a widening of the subsiding branch of the Hadley circulation under greenhouse warming.

Extreme weather and migratory events have been topics of great interest for decades. More recently, a debate has emerged whether the human impact of climate change can lead to armed conflict, and how conflict and extreme climate events interact in inducing large-scale displacement. This paper explores the relationship between conflict and displacement in the context of droughts and floods across Somalia, a country in the East Africa region, in which the population has historically been using migration as coping strategy for the effects of recurring climatic extremes and socio-economic uncertainties. Since 2015, Somalia has been affected by a humanitarian crisis, paired with on-going conflict, which subsequently reduced resilience of its population. Applying panel econometric methods to monthly within-country migration observations from 18 regions together with spatio-temporal conflict and weather data, this paper quantifies the impacts of conflict and extreme weather events on within-country displacement over the period of 2016 to 2018. It combines and analyses conflict-, drought- and flood-related displacement data from the UNHCR-led Protection & Return Monitoring Network (PRMN), disaggregated conflict data from the Armed Conflict Location & Event Data Project (ACLED) with gridded climate estimate data. Empirical evidence suggests significant interaction effects between conflict and extreme weather events on migration, where pre-existing conflict conditions act as accelerators of climate-induced displacement.

Unsaturated fractured aquifer systems offer a domain for complex gravity-driven flow dynamics leading to the development of preferential flow along fracture networks that often strongly contributes to rapid mass fluxes. This behaviour is difficult to recover by volume-effective modeling approaches (e.g. Richards equation) due to the non-linear nature of free-surface flows and mass partitioning processes at unsaturated fracture intersections. The application of well-controlled laboratory experiments enables to isolate single aspects of the mass redistribution process that ultimately affects travel time distributions across scales. We use custom-made acrylic cubes (20 cm x 20 cm x 20 cm) in analogue percolation experiments to create simple fracture networks with single or multiple horizontal fractures. A high precision multichannel dispenser produces gravity-driven free surface flow (droplets; rivulets) at flow rates ranging from 1 ml/min to 5 ml/min. Hereby, total inflow rates are kept constant while the fluid is injected via 15 (droplet flow) or 3 inlets (rivulet flow) to reduce the impact of erratic flow dynamics. Normalized fracture inflow rates (Q_f/Q_0) are calculated and compared for aperture widths d_f of 1 mm and 2.5 mm. A higher efficiency in filling an unsaturated fracture by rivulet flow observed in former studies can be confirmed. The onset of a capillary driven Washburn-type flow is determined and recovered by an analytical solution. In order to upscale the dynamics and enable the prediction of mass partitioning for arbitrary-sized fracture cascades a Gaussian transfer function is derived that reproduces the repetitive filling of fractures, where rivulet flow is the prevailing regime. Results show good agreement with experimental data for all tested aperture widths.

Experimental study of the phase and amplitude observations of sub-ionospheric very low and low frequency signals is performed to analyze the response of the lower ionosphere during the August 21, 2017 total solar eclipse in the United States of America. Three subionospheric wave paths have been investigated. The length of the paths varied from 2200 to 6500 km, signal frequencies were 21.4 kHz, 25.2 kHz and 40.8 kHz. Two paths crossed the region of total eclipse and the third path was in the region of 40-60% of obscuration. None of the signals revealed any noticeable amplitude changes during the eclipse while negative phase anomalies (from -35° to -95°) were detected for all three paths. It was shown that the effective reflection height of the ionosphere in low and middle latitudes has been increased by 3.5-5 km during the eclipse.

Random and small-scale subsurface heterogeneities in velocity and/or density scatter the seismic wavefield when they have scale lengths on the order of the seismic wavelength. Seismic scattering is considered the origin of coda waves. Such inhomogeneities have an important effect on propagating waves, as they generate traveltime and amplitude fluctuations and may be the cause of attenuation or excitation of secondary waves. Understanding the effect of small-scale heterogeneities on the seismic wavefield is important for the characterization of the seismic source (e.g. source parameters of underground nuclear explosions) and to improve our knowledge of the Earth’s structure along the raypath. Several approaches and methods have been suggested to study the scattering of seismic waves and characterise subsurface heterogeneities. Here, we apply a combination of the analysis of the incoherent wavefield component and the coda decay with time to a dataset of over 350 teleseismic events (over 20000 traces) recorded at three seismic arrays (Warramunga, Alice Springs and Pilbara) in Australia. This combination allow us to obtain a series of parameters (correlation length, RMS velocity fluctuations of the heterogeneities and thickness of the scattering layer) that give us a measure of the spatial scale and the magnitude of the heterogeneities present in the lithosphere beneath the arrays. This is the first time such a large dataset is used for a study of these characteristics. Our new results show similar structures and scattering strength for Alice Springs and Warramunga, while revealing a different tectonic signature and stronger scattering in the case of Pilbara, possibly caused by the different thicknesses of crust and lithosphere between these regions and its different tectonic history. These stochastic models of the lithosphere are the first step in the development of a technique analogous to adaptive optics which, in this case, aims at removing the effect of the small-scale, near receiver structure from recorded wavefields, thus enabling us to improve our source characterization and to more clearly image the Earth’s interior.